Fingerprint recognition systems are important tools in security and law enforcement applications. Generally speaking, a digital representation of an image is generated by a fingerprint sensor, etc., which is then digitally processed to create a template of extracted fingerprint features or “minutiae,” such as arches, loops, whorls, etc., that can then be compared with previously stored reference templates for matching purposes. Yet, it is common during the collection process for data corresponding to particular regions or areas of a fingerprint to be compromised as a result of smudging, etc., which results in missing data portions or voids in the fingerprint data field. Such voids decrease the available feature set that can be extracted from the fingerprint data, which in turn reduces the accuracy of the template generated therefrom and potentially compromises the ability to perform correct matching based thereon.
Various interpolation techniques are generally used for filling in missing data in a data field. One such technique is sinc interpolation, which assumes that a signal is band-limited. While this approach may be well suited for communication and audio signals, it may not be as well suited for contoured data, such as fingerprint data. Another approach is polynomial interpolation. This approach is sometimes difficult to implement because the computational overhead may become overly burdensome for higher order polynomials, which may be necessary to provide desired accuracy.
One additional interpolation approach is spline interpolation. While this approach may provide a relatively high reconstruction accuracy, it may also be problematic to implement in contoured data sets because of the difficulty in solving a global spline over the entire model, and because the required matrices may be ill-conditioned. One further drawback of such conventional techniques is that they tend to blur edge content, which may be a significant problem in a fingerprint identification system.
Another approach for filling in regions within an image is set forth in U.S. Pat. No. 6,987,520 to Criminisi et al. This patent discloses an examplar-based filling system which identifies appropriate filling material to replace a destination region in an image and fills the destination region using this material. This is done to alleviate or minimize the amount of manual editing required to fill a destination region in an image. Tiles of image data are “borrowed” from the proximity of the destination region or some other source to generate new image data to fill in the region. Destination regions may be designated by user input (e.g., selection of an image region by a user) or by other means (e.g., specification of a color or feature to be replaced). In addition, the order in which the destination region is filled by example tiles may be configured to emphasize the continuity of linear structures and composite textures using a type of isophote-driven image-sampling process.
Despite the advantages such prior art approaches may provide in certain applications, further advancements may be desirable for filling voids in fingerprint data, for example.